Whether you're optimizing blockchain validators or another performance-critical app, this example shows why continuous profiling belongs in your toolkit from day one.

Grafana is an open-source analytics and monitoring platform that allows users to visualize and analyze metrics from various data sources. The Grafana blog covers topics such as data visualization, monitoring best practices, and new features in Grafana software. Developers and data engineers can learn how to leverage Grafana for monitoring infrastructure, analyzing performance metrics, and creating interactive dashboards for data-driven decision-making.

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A walkthrough of using Grafana Alloy's eBPF-based profiler and Pyroscope to analyze C++ performance bottlenecks in TON blockchain validator code. Using flame graphs and diffs, the team identified hotspots like SHA256 hashing (14% of execution time) and Ed25519 signature verification. Key optimizations included swapping crypto libraries (1.5–3.5% gains), consolidating SHA256 feed calls (20% speedup on DataCell::create), and replacing std::map with std::unordered_set (10% speedup). The post also highlights how eBPF profiling eliminates the need for custom instrumentation code, contrasting it with the manual tracing and memory profilers contestants built themselves.

Finding performance bottlenecks with Pyroscope and Alloy: An example using TON blockchain